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CompletableFuture<T> from Java 8 is an advanced abstraction over a promise that value of type T will be available in the future. Observable<T> is quite similar, but it promises arbitrary number of items in the future, from 0 to infinity. These two representations of asynchronous results are quite similar to the point where Observable with just one item can be used instead of CompletableFuture and vice-versa. On the other hand CompletableFuture is more specialized and because it's now part of JDK, should become prevalent quite soon. Let's celebrate RxJava 1.0 release with a short article showing how to convert between the two, without loosing asynchronous and event-driven nature of them.

From CompletableFuture<T> to Observable<T>CompletableFuture represents one value in the future, so turning it into Observable is rather simple. When Future completes with some value, Observable will emit that value as well immediately and close stream:

ExecutorService abstraction has been around since Java 5. We are talking about 2004 here. Just a quick reminder: both Java 5 and 6 are no longer supported, Java 7 won't be in half a year. The reason I'm bringing this up is that many Java programmers still don't fully understand how ExecutorService works. There are many places to learn that, today I wanted to share few lesser known features and practices. However this article is still aimed toward intermediate programmers, nothing especially advanced.

1. Name pool threads
I can't emphasize this. When dumping threads of a running JVM or during debugging, default thread pool naming scheme is pool-N-thread-M, where N stands for pool sequence number (every time you create a new thread pool, global N counter is incremented) and M is a thread sequence number within a pool. For example pool-2-thread-3 means third thread in second pool created in the JVM lifecycle. See: Executors.defaultThreadFactory(). Not very descriptive. JD…

Hystrix has an advanced feature of collapsing (or batching) requests. If two or more commands run similar request at the same time, Hystrix can combine them together, run one batched request and dispatch split results back to all commands. Let's first see how Hystrix works without collapsing. Imagine we have a service that looks up StockPrice of a given Ticker: